Identification of wrist EMG signals using dry type electrodes

Tadahiro Oyama, Hillary Choge, Stephen Karungaru, Satoru Tsuge, Yasue Mitsukura, Minoru Fukumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Recently, researches of artificial arms and pointing devices using ElectroMyoGram(EMG) have been actively done. However, EMG is usually measured from a part with comparatively big muscular fibers such as arms and shoulders. Therefore, if we can recognize wrist motions using EMG which was measured from the wrist, the range of application will extend furthermore. However, when we use the wrist EMG, there are problems that the individual difference is large and its repeatability is low and so on. In this paper, we aim the construction of wrist EMG recognition system that is robust to these problems.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages4433-4436
Number of pages4
Publication statusPublished - 2009 Dec 1
Externally publishedYes
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: 2009 Aug 182009 Aug 21

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Country/TerritoryJapan
CityFukuoka
Period09/8/1809/8/21

Keywords

  • EMG
  • Neural network
  • Simple-FLDA

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Identification of wrist EMG signals using dry type electrodes'. Together they form a unique fingerprint.

Cite this